arXiv subjects

Dagmar Iber

Publications and source records attributed to Dagmar Iber.

At least 37 records · Page 2Linked to original sources

arXiv2013

Prediction Stability in a data-based mechanistic model of sigmaF during sporulation in Bacillus subtilis

Mathematical modeling of biological networks can help to integrate a large body of information into a consistent framework, which can then be used to arrive at novel mechanistic insight and predictions. We have previously developed a detailed, mechanistic model for the regulation of σF during sporulation in Bacillus subtilis. The model was based on a wide range of quantitative data, and once fitted to the data, the model made predictions that could be confirmed in experiments. However, the analysis was based on a single optimal parameter set. We wondered whether the predictions of the model would be stable for all optimal parameter sets. To that end we conducted a global parameter screen within the physiological parameter ranges. The screening approach allowed us to identify sensitive and sloppy parameters, and highlighted further required datasets during the optimization. Eventually, all parameter sets that reproduced all available data predicted the physiological situation correctly.

q-bio.MN↗

arXiv2013

Inter-dependent Tissue Growth and Turing Patterning in a Model for Long Bone Development

The development of long bones requires a sophisticated spatial organization of cellular signaling, proliferation, and differentiation programs. How such spatial organization emerges on the growing long bone domain is still unresolved. Based on the reported biochemical interactions we developed a regulatory model for the core signaling factors IHH, PTCH1, and PTHrP and included two cell types, proliferating/resting chondrocytes and (pre-)hypertrophic chondrocytes. We show that the reported IHH-PTCH1 interaction gives rise to a Schnakenberg-type Turing kinetics, and that inclusion of PTHrP is important to achieve robust patterning when coupling patterning and tissue dynamics. The model reproduces relevant spatiotemporal gene expression patterns, as well as a number of relevant mutant phenotypes. In summary, we propose that a ligand-receptor based Turing mechanism may control the emergence of patterns during long bone development, with PTHrP as an important mediator to confer patterning robustness when the sensitive Turing system is coupled to the dynamics of a growing and differentiating tissue. We have previously shown that ligand-receptor based Turing mechanisms can also result from BMP-receptor and GDNF-receptor interactions, and that these reproduce the wildtype and mutant patterns during digit formation in limbs and branching morphogenesis in lung and kidneys. Receptor-ligand interactions may thus constitute a general mechanism to generate Turing patterns in nature.

q-bio.TO↗

arXiv2013

The Control of Branching Morphogenesis

Many organs of higher organisms are heavily branched structures and arise by an at first sight similar process of branching morphogenesis. Yet the regulatory components and local interactions that have been identified differ greatly in these organs. It is an open question whether the regulatory processes work according to a common principle and in how far physical and geometric constraints determine the branching process. Here we review the known regulatory factors and physical constraints in lung, kidney, pancreas, prostate, mammary and salivary gland branching morphogenesis, and describe the models that have been formulated to analyse their impacts.

q-bio.TO↗

arXiv2013

Simulation of a Microfluidic Gradient Generator using Lattice Boltzmann Methods

Microfluidics provides a powerful and versatile technology to accurately control spatial and temporal conditions for cell culturing and can therefore be used to study cellular responses to gradients. Here we use Lattice Boltzmann methods (LBM) to solve both the Navier-Stokes equation (NSE) for the fluid and the coupled convection-diffusion equation (CDE) for the compounds that form the diffusion-based gradient. The design of a microfluidic chamber for diffusion-based gradients must avoid flow through the cell chamber. This can be achieved by alternately opening the source and the sink channels. The fast toggling of microfluidic valves requires switching between different boundary conditions. We demonstrate that the LBM is a powerful method for handling complex geometries, high Peclet number conditions, discontinuities in the boundary conditions, and multiphysics coupling.

physics.flu-dyn↗

arXiv2013

Dynamic Image-Based Modelling of Kidney Branching Morphogenesis

Kidney branching morphogenesis has been studied extensively, but the mechanism that defines the branch points is still elusive. Here we obtained a 2D movie of kidney branching morphogenesis in culture to test different models of branching morphogenesis with physiological growth dynamics. We carried out image segmentation and calculated the displacement fields between the frames. The models were subsequently solved on the 2D domain, that was extracted from the movie. We find that Turing patterns are sensitive to the initial conditions when solved on the epithelial shapes. A previously proposed diffusion-dependent geometry effect allowed us to reproduce the growth fields reasonably well, both for an inhibitor of branching that was produced in the epithelium, and for an inducer of branching that was produced in the mesenchyme. The latter could be represented by Glial-derived neurotrophic factor (GDNF), which is expressed in the mesenchyme and induces outgrowth of ureteric branches. Considering that the Turing model represents the interaction between the GDNF and its receptor RET very well and that the model reproduces the relevant expression patterns in developing wildtype and mutant kidneys, it is well possible that a combination of the Turing mechanism and the geometry effect control branching morphogenesis.

q-bio.TO↗

arXiv2013

Kidney branching morphogenesis under the control of a ligand-receptor based Turing mechanism

The main signalling proteins that control early kidney branching have been defined. Yet the underlying mechanism is still elusive. We have previously shown that a Schnakenberg-type Turing mechanism can recapitulate the branching and protein expression patterns in wildtype and mutant lungs, but it is unclear whether this mechanism would extend to other branched organs that are regulated by other proteins. Here we show that the GDNF-RET regulatory interaction gives rise to a Schnakenberg-type Turing model that reproduces the observed budding of the ureteric bud from the Wolffian duct, its invasion into the mesenchyme, and the observed branching pattern. The model also recapitulates all relevant protein expression patterns in wild-type and mutant mice. The lung and kidney models are both based on a particular receptor- ligand interaction and require: (1) cooperative binding of ligand and receptor, (2) a lower diffusion coefficient for the receptor than for the ligand, and (3) an increase in the receptor concentration in response to receptor-ligand binding (by enhanced transcription, more recycling or similar). These conditions are met also by other receptor-ligand systems. We propose that ligand-receptor based Turing patterns represent a general mechanism to control branching morphogenesis and other developmental processes.

q-bio.TO↗

arXiv2013

Simulating Tissue Morphogenesis and Signaling

During embryonic development tissue morphogenesis and signaling are tightly coupled. It is therefore important to simulate both tissue morphogenesis and signaling simultaneously in in silico models of developmental processes. The resolution of the processes depends on the questions of interest. As part of this chapter we will introduce different descriptions of tissue morphogenesis. In the most simple approximation tissue is a continuous domain and tissue expansion is described according to a pre-defined function of time (and possibly space). In a slightly more advanced version the expansion speed and direction of the tissue may depend on a signaling variable that evolves on the domain. Both versions will be referred to as 'prescribed growth'. Alternatively tissue can be regarded as incompressible fluid and can be described with Navier-Stokes equations. Local cell expansion, proliferation, and death are then incorporated by a source term. In other applications the cell boundaries may be important and cell-based models must be introduced. Finally, cells may move within the tissue, a process best described by agent-based models.

q-bio.TO↗

arXiv2013

Digit patterning during limb development as a result of the BMP-receptor interaction

Turing models have been proposed to explain the emergence of digits during limb development. However, so far the molecular components that would give rise to Turing patterns are elusive. We have recently shown that a particular type of receptor-ligand interaction can give rise to Schnakenberg-type Turing patterns, which reproduce patterning during lung and kidney branching morphogenesis. Recent knock-out experiments have identified Smad4 as a key protein in digit patterning. We show here that the BMP-receptor interaction meets the conditions for a Schnakenberg-type Turing pattern, and that the resulting model reproduces available wildtype and mutant data on the expression patterns of BMP, its receptor, and Fgfs in the apical ectodermal ridge (AER) when solved on a realistic 2D domain that we extracted from limb bud images of E11.5 mouse embryos. We propose that receptor-ligand-based mechanisms serve as a molecular basis for the emergence of Turing patterns in many developing tissues.

q-bio.TO↗

arXiv2012

Simulation Organogenesis in COMSOL: Deforming and Interacting Domains

Organogenesis is a tightly regulated process that has been studied experimentally for decades. We are developing mechanistic models for the morphogenesis of limbs, lungs, and kidneys with a view to integrate available knowledge and to better understand the underlying regulatory logic. In our previous paper on simulating organogenesis in COMSOL (German et al COMSOL Conf Procedings 2011) we discussed methods to efficiently solve such models, predominantly on a static domain. Organ size, however, changes dramatically during development, and tissues are composed of several layers that may expand both together or independently. Moreover, the developing organ are typically embedded in an environment, and diffusional exchange with this environment can affect the patterning process. Here we discuss methods to build and efficiently solve models involving large deformation of composite domains in COMSOL Multiphysics.

q-bio.TO↗

arXiv2012

Simulations demonstrate a simple network to be sufficient to control branch point selection, smooth muscle and vasculature formation during lung branching morphogenesis

Proper lung functioning requires not only a correct structure of the conducting airway tree, but also the simultaneous development of smooth muscles and vasculature. Lung branching morphogenesis is strongly stereotyped and involves the recursive use of only three modes of branching. We have previously shown that the experimentally described interactions between Fibroblast growth factor (FGF)10, Sonic hedgehog (SHH) and Patched (Ptc) can give rise to a Turing mechanism that not only reproduces the experimentally observed wildtype branching pattern but also, in part counterintuitive, patterns in mutant mice. Here we show that, even though many proteins affect smooth muscle formation and the expression of Vegfa, an inducer of blood vessel formation, it is sufficient to add FGF9 to the FGF10/SHH/Ptc module to successfully predict simultaneously the emergence of smooth muscles in the clefts between growing lung buds, and Vegfa expression in the distal sub-epithelial mesenchyme. Our model reproduces the phenotype of both wildtype and relevant mutant mice, as well as the results of most culture conditions described in the literature.

q-bio.TO↗

arXiv2012

Branch Mode Selection during Early Lung Development

Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modes

q-bio.TO↗

arXiv2012

Spatial organization of proteomes: A low-rank approximation

We investigate the problem of signal transduction via a descriptive analysis of the spatial organization of the complement of proteins exerting a certain function within a cellular compartment. We propose a scheme to assign a numerical value to individual proteins in a protein interaction network by means of a simple optimization algorithm. We test our procedure against datasets focusing on the proteomes in the neurite and soma compartments.

q-bio.MN↗

arXiv2012

Simulating Organogenesis in COMSOL

Organogenesis is a tightly regulated process that has been studied experimentally for decades. Computational models can help to integrate available knowledge and to better understand the underlying regulatory logic. We are currently studying mechanistic models for the development of limbs, lungs, kidneys, and bone. We have tested a number of alternative methods to solve our spatio- temporal differential equation models of reaction-diffusion type on growing domains of realistic shape, among them finite elements in COMSOL Multiphysics. Given the large number of variables (up to fifteen), the sharp domain boundaries, the travelling wave character of some solutions, and the stiffness of the reactions we are facing numerous numerical challenges. To test new ideas efficiently we have developed a strategy to optimize simulation times in COMSOL.

q-bio.TO↗

arXiv2011

The plasticity of TGF-beta signaling

The family of TGFb ligands is large and its members are involved in many different signaling processes. These signaling processes strongly differ in type with TGFb ligands eliciting both sustained or transient responses. Members of the TGFb family can also act as morphogen and cellular responses would then be expected to provide a direct read-out of the extracellular ligand concentration. We were interested to define the set of minimal modifications that are required to change the type of signal processing in the TGFb signaling network. To define the key aspects for signaling plasticity we focused on the core of the TGFb signaling network. With the help of a parameter screen we identified ranges of kinetic parameters and protein concentrations that give rise to transient, sustained, or oscillatory responses to constant stimuli, as well as those parameter ranges that enable a proportional response to time-varying ligand concentrations (as expected in the read-out of morphogens). A combination of a strong negative feedback and fast shuttling to the nucleus biases signaling to a transient rather than a sustained response, while oscillations were obtained if ligand binding to the receptor is weak and the turn-over of the I-Smad is fast. A proportional read-out required inefficient receptor activation in addition to a low affinity of receptor-ligand binding. We find that targeted modification of single parameters suffices to alter the response type. The architecture of the TGFb pathway enables the observed signaling plasticity. The observed range of signaling outputs to TGFb ligand in different cell types and under different conditions can be explained with differences in cellular protein concentrations and with changes in effective rate constants due to cross-talk with other signaling pathways.

q-bio.MN↗

arXiv2011

A computational analysis of the dynamic roles of talin, Dok1, and PIPKI for integrin activation

Integrin signaling regulates cell migration and plays a pivotal role in developmental processes and cancer metastasis. Integrin signaling has been studied extensively and much data is available on pathway components and interactions. Yet the data is fragmented and an integrated model is missing. We use a rule-based modeling approach to integrate available data and test biological hypotheses regarding the role of talin, Dok1 and PIPKI in integrin activation. The detailed biochemical characterization of integrin signaling provides us with measured values for most of the kinetics parameters. However, measurements are not fully accurate and the cellular concentrations of signaling proteins are largely unknown and expected to vary substantially across different cellular conditions. By sampling model behaviors over the physiologically realistic parameter range we find that the model exhibits only two different qualitative behaviours and these depend mainly on the relative protein concentrations, which offers a powerful point of control to the cell. Our study highlights the necessity to characterize model behavior not for a single parameter optimum, but to identify parameter sets that characterize different signaling modes.

q-bio.MN↗

arXiv2010

A Monte Carlo study of ligand-dependent integrin signal initiation

Integrins are allosteric cell adhesion receptors that control many important processes, including cell migration, proliferation, and apoptosis. Ligand binding activates integrins by stabilizing an integrin conformation with separated cytoplasmic tails, thus enabling the binding of proteins that mediate cytoplasmic signaling. Experiments demonstrate a high sensitivity of integrin signaling to ligand density and this has been accounted mainly to avidity effects. Based on experimental data we have developed a quantitative Monte Carlo model for integrin signal initiation. We show that within the physiological ligand density range avidity effects cannot explain the sensitivity of cellular signaling to small changes in ligand density. Src kinases are among the first proteins to be activated, possibly by trans auto-phosphorylation. We calculate the extent of integrin and ligand clustering as well as the speed and extent of Src kinase activation by trans auto-phosphorylation or direct binding at different experimentally monitored ligand densities. We find that the experimentally observed ligand density dependency can be reproduced if Src kinases are activated by trans auto-phosphorylation or some other mechanism limits integrin-dependent Src kinase activation. We propose that Src kinase and thus cell activation by trans auto-phosphorylation may provide a mechanism to enable ligand-density dependent responses at physiological ligand densities. The capacity to detect small differences in ligand density at a ligand density that is large enough to permit cell adhesion is likely to be important for haptotaxis.

q-bio.QM↗

arXiv2006

An analysis of B cell selection mechanisms in germinal centers

Affinity maturation of antibodies during immune responses is achieved by multiple rounds of somatic hypermutation and subsequent preferential selection of those B cells that express B cell receptors with improved binding characteristics for the antigen. The mechanism underlying B cell selection has not yet been defined. By employing an agent-based model, we show that for physiologically reasonable parameter values affinity maturation can neither be driven by competition for binding sites nor antigen -- even in the presence of competing secreted antibodies. Within the tested mechanisms, only clonal competition for T cell help or a refractory time for the interaction of centrocytes with follicular dendritic cells are found to enable affinity maturation while generating the experimentally observed germinal center characteristics and tolerating large variations in the initial antigen density.

q-bio.CB↗

arXiv2006

A quantitative study of the benefits of co-regulation using the spoIIA operon as an example

The distribution of most genes is not random, and functionally linked genes are often found in clusters. Several theories have been put forward to explain the emergence and persistence of operons in bacteria. Careful analysis of genomic data favours the co-regulation model, where gene organization into operons is driven by the benefits of coordinated gene expression and regulation. Direct evidence that co-expression increases the individual's fitness enough to ensure operon formation and maintenance is, however, still lacking. Here, a previously described quantitative model of the network that controls the transcription factor sigmaF during sporulation in Bacillus subtilis is employed to quantify the benefits arising from both organisation of the sporulation genes into the spoIIA operon and from translational coupling. The analysis shows that operon organization, together with translational coupling, is important because of the inherent stochastic nature of gene expression which skews the ratios between protein concentrations in the absence of co- regulation. The predicted impact of different forms of gene regulation on fitness and survival agrees quantitatively with published sporulation efficiencies.

q-bio.MN↗